OBJECTIVES:

Digital Therapeutics (DTx) are medical interventions directly to patients using evidence-based, clinically evaluated software to treat, manage, and prevent a broad spectrum of diseases and disorders.

Randomized clinical trials are a source of DTx evidence, similar to pharmaceuticals or medical devices. In addition, the use of real-world evidence (RWE) has been increasingly explored for DTx value demonstration. Key concerns around the use of RWE in DTx, has thus far limited its acceptance and applicability, including the robustness of data, and a lack of consensus over an evaluation framework for DTx.

This study aims to understand the current trends in evidence development for DTx, and to evaluate how this may impact the assessment of these therapies. The analysis will describe the strength and influence that different types of evidence and endpoints have had in the value assessment, coverage, reimbursement, and adoption of DTx.

METHODS:

A targeted literature review was conducted to understand the evidence developed and submitted as a part of DTx commercialization. Sources included PubMed, the ISPOR presentations database, clinicaltrials.gov, and gray literature (e.g., thought leadership sources).

RESULTS:

Based on an interim analysis, publications were identified across all the targeted sources, PubMed (66), ClinicalTrials.gov (314) and ISPOR database (343). Through these studies, the importance of real-world clinical evidence in the value assessment, coverage, reimbursement, and adoption of DTx was validated, together with claims data to justify the economic impact of DTx. Additionally, this research identified the endpoints that could drive value perception for DTx from a holistic perspective (clinical, economic, patient, societal).

CONCLUSIONS:

Future DTx are expected to provide a combination of clinical trials, real-world evidence, and RWE to support clinical and economical value of the DTx, and provide detailed findings in terms of patient engagement, change from baseline status and impact on healthcare resource utilization.